• DocumentCode
    1926057
  • Title

    Estimation of Node Localization with a Real-Coded Genetic Algorithm in WSNs

  • Author

    Nan, Guo-fang ; Li, Min-qiang ; Li, Jie

  • Author_Institution
    Tianjin Univ., Tianjin
  • Volume
    2
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    873
  • Lastpage
    878
  • Abstract
    Location knowledge of sensor nodes in a network is essential for many tasks such as routing, cooperative sensing, or service delivery in ad hoc, mobile, or sensor networks, and it is hard to get the precision solution by traditional node localization algorithm, while genetic algorithm is an effective methodology for solving combinatorial optimization problems, so, in this paper, a real-coded version of the commonly used genetic algorithm is described in order to evaluate the precision of node localization problem in wireless sensor networks, meanwhile, the corresponding fitness function and genetic operators are designed. The algorithms presented in this paper are validated on a combined Windows XP and MATLAB simulation on a sensor network with fixed number of nodes whose distance measurements are corrupted by Gaussian noise. The results show that the proposed scheme gives accurate location of nodes.
  • Keywords
    combinatorial mathematics; genetic algorithms; wireless sensor networks; Gaussian noise; combinatorial optimization problems; cooperative sensing; fitness function; genetic operators; location knowledge; node localization estimation; real-coded genetic algorithm; wireless sensor networks; Application software; Cybernetics; Genetic algorithms; Genetic engineering; Global Positioning System; Intelligent networks; Machine learning; Sensor phenomena and characterization; Sensor systems; Wireless sensor networks; Genetic algorithm; Node localization; Positioning systems; Wireless sensor network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370265
  • Filename
    4370265